Geoff And Francis

Specifying the inclusion and exclusion criteria for systematic literature review...

Starting your inclusion and exclusion criteria before you conduct the review is important. This section is  Where you describe the criteria that you will be using to include any research studies in your review. Torgerson (2003) suggests that a high quality systematic review should have inclusion and exclusion Criteria that are ‘rigorously and transparently reported a priori (before you start the review) ‘(Torgerson 2003:26). You may well ask ‘ Why is it necessary’? The reason is so that your search can target the Papers that will answer your questions and exclude any irrelevant ones. The criteria need to be explicit And applied stringently. The criteria you will need to describe the types of research studies you will be Including , the participants, the interventions, comparative groups and outcome measures. PICO now Becomes PICOT. For qualitative systematic reviews use PEO( which will now become PEOT). read...

How to Formulate a Research Problem in your PhD Research Proposal...

There are two types of research problems, viz., those which relate  to states of nature and those which relate to relationships between variables. At the very outset, the researcher must single out the problem he wants to study, i.e, he must decide the general area of interest or aspect of a subject matter that he would like to inquire into. Initially, the problem may be stated in a broad general way and then the ambiguities, if any related to the problem, are resolved. Then the feasibility of a particular solution has to be considered before a working formulation of the problem can be set up. The formulation of a general topic into a specific research problem, thus constitutes the first step in a scientific inquiry. Essentially two steps are involved in formulating the research problem, viz., understanding the problem thoroughly, and rephrasing the same into meaningful terms from an analytical point of view.    read...

Preparing for Interviews – Guide for Qualitative Research...

There are many different types of question that can be asked and in many different ways. What is common to all questions, though, is that they must be worded in a way that is understood by the respondents and to which respondents can relate. This means ensuring that there are minority-language versions of the questionnaire if the sample is likely to include people who speak a language is unlikely to be sufficiently good to be able to complete an interview in it. By denying sections of the survey population the opportunity to participate in the study, the questionnaire writer is effectively disenfranchising them from influencing the findings. For many studies commissioned by the public sector in countries, it is important that the interview is capable of being conducted in any language that is spoken by a significant number of people in the any language that is the spoken by a significant number of people in the survey population to avoid the danger of disenfranchisement. In the UK Many government studies require questionnaire versions in Welsh, Urdu, Hindi and other languages, and in USA a Spanish-language version will often be required. read...

A Comprehensive Guide to Performing Systematic Literature Review...

With growing importance of research, huge amount of studies, often with conflicting findings are being published every year. The difference in the findings may occur due to sample variation or any other flaws. In such situations, identifying the most reliable results can be confusing. Literature reviews are performed with varying standards, ranging from annotated bibliography to rigorously synthesising scientific body of research. One such rigorous approach is systematic literature review (SLR).  read...

An introduction to Data Mining & its Applications in Bioinformatics...

With the increasing importance of bioinformatics in agriculture, molecular medicine, microbial genome applications, etc. the research in this field has gained momentum than ever before. Bioinformatics, also known as computational biology, deals with interpreting biological data by using computer science and information technology. Of lately, research in bioinformatics has produced vast amounts of data and will continue to generate proteomic, genomic, etc. data. To analyze and gain deep insights into such biological data necessitates making sense of the information by inferring the data. For instance, gene classification, protein structure prediction, clustering of gene expression data, protein-protein interactions, etc. These processes, in turn, increases the need for interaction between bioinformatics and data mining.   read...

Spoiler Alert Ahead: 6 Great Steps for Conducting Factor Analysis using SPSS...

Statistics, a scientific approach to investigating statistical data, is employed to determine associations among the phenomena to define, predict and control their occurrence. To successfully perform statistical tests, it is a must to identify the underlying factors or variables under study. This is when the factor analysis comes into the picture.   Factor analysis, known as a dimension reduction technique, helps to reduce the dimension creating new factors from the old ones by checking the correlations and eigenvalue.  read...

One-Way MANOVA Test: How to Assess If Mean Differences Exist Between the Samples Using SPSS?...

It is extended version an ANOVA with two or more dependent variables. ANOVA test is used for evaluating the difference in means between two or more related groups, while a MANOVA test is used for evaluating the difference in two or more vectors of factors.  ASSUMPTIONS: All the observations should be statistically independent. We should have an adequate sample size. As a larger sample size, the better it is. We should be having more cases than the number of variables in each group. In ANOVA, the Dependent variables are normally distributed within the group. whereas in MANOVA,the Dependent variables have multivariate normality within the groups. There are no univariate or multivariate outliers. Univariate outliers are often just called outliers.In one-way MANOVA, we see how to:         (1) detect univariate outliers using box plots using SPSS statistics in order to check outliers         (2) check for multivariate outliers using Mahalanobis distance, which we can do in SPSS  read...
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